News

A team of interdisciplinary researchers has discovered a new technique to store information in DNA – in this case "The Wizard of Oz," translated into Esperanto – with unprecedented accuracy and efficiency. The technique harnesses the information-storage capacity of intertwined strands of DNA to encode and retrieve information in a way that is both durable and compact. The technique is described in a paper in this week's Proceedings of the National Academy of Sciences.

University of Texas at Austin computer science researcher Kristen Grauman was selected as a finalist for the 2020 Blavatnik National Awards for Young Scientists.

The datasets used by many software applications can be represented as graphs, defined by sets of vertices and edges. These graphs are rich with useful information, and can be used to determine patterns and relationships among the stored data. This process of discovering relevant patterns from graphs is called Graph Pattern Mining. A team of Texas Computer Science (TXCS) researchers advised by Dr. Keshav Pingali has done groundbreaking work to make these programs more efficient and accessible. Their work was recently accepted to Very Large Databases (VLDB) 2020, one of the premier conferences in computer science.

A message from Dean Paul Goldbart to the College of Natural Sciences community underscores the need to stand in solidarity and support one another. This post was updated on Tuesday, June 2 to include a statement from the CNS Diversity and Inclusion Committee.

Texas Computer Science (TXCS) graduate students Garrett Bingham and William Macke, under the advisement of TXCS professor Risto Miikkulainen, are contributing to the improvement of AI with their research. Their paper, entitled "Evolutionary Optimization of Deep Learning Activation Functions" was accepted into the 2020 Genetic and Evolutionary Computation Conference. The work concerns the evolutionary optimization of activation functions as a potential means of improving neural networks, which may ultimately lead to the creation of smarter and more accurate AI.

Each year, the College of Natural Sciences bestows its highest honors for graduating seniors on a select group of students. These students, known as Dean's Honored Graduates demonstrate excellence across multiple domains, achieving not only academically but in scientific research, independent intellectual pursuits, leadership, service, entrepreneurship and community building. Below are biographies of the 30 outstanding students selected by a committee of College of Natural Sciences faculty for this distinction in 2020.

Students at UT Austin already had plenty on their plates. When COVID-19 hit, the usual return from spring break and settling back into campus life turned instead into a mass migration—students scattering to shelter in place wherever they call home, in many cases moving back in with their families. Some became ill or began caring for sick family members. Classes moved online. Jobs ended. Everything was topsy turvy (it still is). But that hasn't stopped College of Natural Sciences undergraduates in public health, neuroscience and computer science from finding ways to help out their communities and fellow classmates.

The promise of artificial intelligence to solve problems in drug design, discover how babies learn language, and make progress in many other areas has been stymied by the inability of humans to understand what's going on inside AI systems.

Artificial intelligence is becoming more and more a part of our daily lives. But will AI have mostly positive or negative impacts on society?